Understanding observability metrics: Types, golden signals, and best practices

Observability metrics are essential for understanding the performance, behavior, and health of applications and systems, as they enable organizations to make sense of their operations and develop proactive monitoring processes. These metrics are part of a broader observability framework, traditionally composed of three pillars—metrics, logs, and traces—with a fourth pillar, profiling, emerging as technology advances. Key types of observability metrics include application, system, and business metrics, each providing insights into different aspects of a technology stack's performance. The Site Reliability Engineering (SRE) community emphasizes the "four golden signals" of latency, traffic, errors, and saturation as critical for effective observability. Challenges in implementing observability metrics include managing data heterogeneity and noise, which can be addressed by defining clear objectives, using open standards like OpenTelemetry, leveraging automation, and customizing visualizations. Elastic Observability offers a unified solution for collecting, monitoring, and analyzing these metrics, enhancing operational efficiency and enabling faster resolution of issues.